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Modeling traffic congestion spreading using a topology-based SIR epidemic model.

Kozabek, A., Chai, W. K. and Zheng, G., 2024. Modeling traffic congestion spreading using a topology-based SIR epidemic model. IEEE Access. (In Press)

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Modeling_traffic_congestion_spreading_using_a_topology-based_SIR_epidemic_model.pdf - Published Version
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DOI: 10.1109/ACCESS.2024.3370474


The continuous urbanisation and increase in vehicle ownership have increasingly exacerbated traffic congestion problems. In this paper, we advocate the use of epidemic theory to model the spreading of traffic congestion in urban cities. Specifically, we use the Susceptible-Infected-Recovered (SIR) model but propose to explicitly consider the road network structure in the model to understand the contagion process of road congestion. This departs from the classical SIR model where homogeneous mixing based on the law of mass action is assumed. For this purpose, we adopt the N-intertwined modeling framework for the SIR model based on continuous-time Markov chain analysis. In our evaluation, we used two real-world traffic datasets collected in California and Los Angeles. We compare our results against both classical and average-degreebased SIR models. Our results show better agreement between the model and actual congestion conditions and shed light on how congestion propagates across a road network. We see the potential application of insights gained from this work on the development of traffic congestion mitigation strategies.

Item Type:Article
Uncontrolled Keywords:Congestion spread modelling; epidemics; SIR model; Topology; Traffic congestion; urban road networks
Group:Faculty of Science & Technology
ID Code:39531
Deposited By: Symplectic RT2
Deposited On:29 Feb 2024 11:26
Last Modified:04 Mar 2024 13:35


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